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Record W4385513927 · doi:10.1002/adma.202304751

Flexible Carbon Nanotube‐Epitaxially Grown Nanocrystals for Micro‐Thermoelectric Modules

2023· article· en· W4385513927 on OpenAlexaff
Qun Jin, Yang Zhao, Xuehao Long, Song Jiang, Cheng Qian, Feng Ding, Ziqiang Wang, Xiaoqi Li, Zhi Yu, Juan He, Yujie Song, Hailong Yu, Ye Wan, Kaiping Tai, Ning Gao, Jun Tan, Chang Liu, Hui–Ming Cheng

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsInstitute of Particle Physics
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceCarbon nanotubeThermoelectric effectMicroelectronicsOptoelectronicsEpitaxyThermal conductivityNanotechnologyThermoelectric materialsComposite material

Abstract

fetched live from OpenAlex

Abstract Flexible thermoelectric materials have attracted increasing interest because of their potential use in thermal energy harvesting and high‐spatial‐resolution thermal management. However, a high‐performance flexible micro‐thermoelectric device (TED) compatible with the microelectronics fabrication process has not yet been developed. Here a universal epitaxial growth strategy is reported guided by 1D van der Waals‐coupling, to fabricate freestanding and flexible hybrids comprised of single‐wall carbon nanotubes and ordered (Bi,Sb) 2 Te 3 nanocrystals. High power factors ranging from ≈1680 to ≈1020 µW m −1 K −2 in the temperature range of 300–480 K, combined with a low thermal conductivity yield a high average figure of merit of ≈0.81. The fabricated flexible micro‐TED module consisting of two p–n couples of freestanding thermoelectric hybrids has an unprecedented open circuit voltage of ≈22.7 mV and a power density of ≈0.36 W cm −2 under ≈30 K temperature difference, and a net cooling temperature of ≈22.4 K and a heat absorption density of ≈92.5 W cm −2 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2023
Admission routes1
Has abstractyes

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